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Kenji Konishi

from San Jose, CA
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Related to:
Megumi Konishi
Connected to:
Daisuke Konishi, 63Katsuyuki Konishi, 61Ryo Konishi, 75Saori Konishi, 44Kristen M Konisiewicz, 42Richard J Konisiewicz, 71Michael A Konisky, 81Jane A Koniszewski, 74Nicole Konitski, 44Phyllis P Konitshek, 85

Kenji Konishi Phones & Addresses

  • San Jose, CA

Resumes

Resumes

Kenji Konishi Photo 1

Research Manager And System Architect

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Location:
San Jose, CA
Industry:
Electrical/Electronic Manufacturing
Work:
Denso International America
Research Manager and System Architect
Denso Oct 2012 - Mar 2015
System Architect
Sharp Electronics May 2010 - Jun 2012
Pre-Sales Architect
Sharp Electronics Jun 2006 - May 2010
Project Leader
Sharp Electronics Apr 1998 - May 2006
Engineer
Education:
Tokyo University of Agriculture and Technology 1992 - 1998
Masters, Electronics
Skills:
Software Development
Business Development
Mobile Devices
Communication Protocols
Vehicle Tracking
Embedded Systems
Product Management
Languages:
Japanese
English
Kenji Konishi Photo 2

Kenji Konishi

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Publications

Us Patents

Application Specific Connected Service Provision System

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US Patent:
20190280954, Sep 12, 2019
Filed:
Jan 23, 2019
Appl. No.:
16/255507
Inventors:
- Southfield MI, US
- Kariya-city, JP
Kenji KONISHI - San Jose CA, US
International Classification:
H04L 12/26
H04W 4/40
G06N 7/00
Abstract:
A vehicle application enabling system is provided and includes a memory and initialization, latency evaluation, and application enable modules. The initialization module: receives a maximum network latency; sets a percentage of occurrences that the maximum network latency is not satisfied, a maximum false positive rate, and a maximum deviation value; and calculates a weighting factor based on the percentage of occurrences, maximum false positive rate and maximum deviation value. The latency evaluation module implements a latency evaluation algorithm, which includes: comparing one or more latency estimates to the maximum network latency to provide one or more samples; updating confusion matrix statistics based on the one or more samples; updating a probability threshold based on the maximum false positive rate; updating weighted observations based on the weighting factor; and determining a predicted decision based on the probability threshold. The application enable module executes the vehicle application based on the probability threshold.
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Kenji Konishi from San Jose, CA Get Report